Explore the vast range of titles available.

Background Verbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment. Methods We randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naïve Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one (4651) deaths were allocated to physician (standard), and 4723 to automated arms. Results The two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79–45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm. Conclusions While desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths. Trial registration ClinicalTrials.gov , NCT02810366. Submitted on 11 April 2016.

Verbal autopsy (VA) deals with post-mortem surveys about deaths, mostly in low and middle income countries, where the majority of deaths occur at home rather than a hospital, for retrospective assignment of causes of death (COD) and subsequently evidence-based health system strengthening. Automated algorithms for VA COD assignment have been developed and their performance has been assessed against physician and clinical diagnoses. Since the performance of automated classification methods remains low, we aimed to enhance the Naïve Bayes Classifier (NBC) algorithm to produce better ranked COD classifications on 26,766 deaths from four globally diverse VA datasets compared to some of the leading VA classification methods, namely Tariff, InterVA-4, InSilicoVA and NBC. We used a different strategy, by training multiple NBC algorithms using the one-against-all approach (OAA-NBC). To compare performance, we computed the cumulative cause-specific mortality fraction (CSMF) accuracies for population-level agreement from rank one to five COD classifications. To assess individual-level COD assignments, cumulative partially-chance corrected concordance (PCCC) and sensitivity was measured for up to five ranked classifications. Overall results show that OAA-NBC consistently assigns CODs that are the most alike physician and clinical COD assignments compared to some of the leading algorithms based on the cumulative CSMF accuracy, PCCC and sensitivity scores. The results demonstrate that our approach improves the performance of classification (sensitivity) by between 6% and 8% compared with other VA algorithms. Population-level agreements for OAA-NBC and NBC were found to be similar or higher than the other algorithms used in the experiments. Although OAA-NBC still requires improvement for individual-level COD assignment, the one-against-all approach improved its ability to assign CODs that more closely resemble physician or clinical COD classifications compared to some of the other leading VA classifiers.

More than three billion people rely on seafood for nutrition. However, fish are the predominant source of human exposure to methylmercury (MeHg), a potent neurotoxic substance. In the United States, 82% of population-wide exposure to MeHg is from the consumption of marine seafood and almost 40% is from fresh and canned tuna alone 1 . Around 80% of the inorganic mercury (Hg) that is emitted to the atmosphere from natural and human sources is deposited in the ocean 2 , where some is converted by microorganisms to MeHg. In predatory fish, environmental MeHg concentrations are amplified by a million times or more. Human exposure to MeHg has been associated with long-term neurocognitive deficits in children that persist into adulthood, with global costs to society that exceed US$20 billion 3 . The first global treaty on reductions in anthropogenic Hg emissions (the Minamata Convention on Mercury) entered into force in 2017. However, effects of ongoing changes in marine ecosystems on bioaccumulation of MeHg in marine predators that are frequently consumed by humans (for example, tuna, cod and swordfish) have not been considered when setting global policy targets. Here we use more than 30 years of data and ecosystem modelling to show that MeHg concentrations in Atlantic cod ( Gadus morhua ) increased by up to 23% between the 1970s and 2000s as a result of dietary shifts initiated by overfishing. Our model also predicts an estimated 56% increase in tissue MeHg concentrations in Atlantic bluefin tuna ( Thunnus thynnus ) due to increases in seawater temperature between a low point in 1969 and recent peak levels—which is consistent with 2017 observations. This estimated increase in tissue MeHg exceeds the modelled 22% reduction that was achieved in the late 1990s and 2000s as a result of decreased seawater MeHg concentrations. The recently reported plateau in global anthropogenic Hg emissions 4 suggests that ocean warming and fisheries management programmes will be major drivers of future MeHg concentrations in marine predators. Overfishing and warming ocean temperature have caused an increase in methylmercury concentrations in some Atlantic predatory fish, and this trend is predicted to continue unless stronger mercury and carbon emissions standards are imposed.

A large-scale treatment–control meta-analysis of US fisheries provides evidence that the implementation of catch shares extend fishing seasons by slowing the race to fish. No catch to sharing fish In fisheries, the competitive race to fish reduces fishing season length, threatens fish stocks and leads to ecological damage, economic waste and safety risks. Catch shares—whereby fishermen, fishing vessels or cooperatives are allocated a portion of the total allowable catch—are thought to slow the race to fish, but evidence to date has been limited to individual fisheries. In this meta-analysis, Martin Smith and colleagues show that the beneficial effect of catch shares on the race to fish holds true across 39 fisheries in the US. They suggest that these findings can inform the current debate over the expansion of market-based regulatory measures, such as catch shares, in fisheries. In fisheries, the tragedy of the commons manifests as a competitive race to fish that compresses fishing seasons, resulting in ecological damage, economic waste, and occupational hazards 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 . Catch shares are hypothesized to halt the race by securing each individual’s right to a portion of the total catch, but there is evidence for this from selected examples only 2 , 9 . Here we systematically analyse natural experiments to test whether catch shares reduce racing in 39 US fisheries. We compare each fishery treated with catch shares to an individually matched control before and after the policy change. We estimate an average policy treatment effect in a pooled model and in a meta-analysis that combines separate estimates for each treatment–control pair. Consistent with the theory that market-based management ends the race to fish, we find strong evidence that catch shares extend fishing seasons. This evidence informs the current debate over expanding the use of market-based regulation to other fisheries.

The Eastern Baltic cod ( Gadus morhua ) stock is currently in a very poor state, with low biomass and adverse trends in several life history and demographic parameters. This raises concern over whether and to what level recovery is possible. Here, we look for new insights from a historical perspective, extending the time series of various stock health indicators back to the 1940s, i.e. to the beginning of intensive exploitation of the Eastern Baltic cod. The historical data confirm that the stock deterioration in recent years is unprecedented, as all indicators are presently in their worst states on record. Cod body condition and energy reserves were equally low in the 1940s–1950s, accompanied by high parasitic liver worm infection, comparable to that measured in recent years. However, other stock parameters (size structure, size at maturity, stock distribution) are currently in their worst states over the past 80 years. In contrast, the state of cod in the 1970s to early 1990s that is often perceived as a desirable target, was exceptional, with the most favorable indicator levels in the time series. Long-term observation data reveal concurrent or asynchronous trends in different indicators of stock health and to what extent these have coincided with changes in possible external drivers. In this way, the extended time series contribute to ongoing research on understanding the collapse of the cod and its recovery potential.

Lumpfish (Cyclopterus lumpus) is a transatlantic marine fish displaying large population sizes and a high potential for dispersal and gene-flow. These features are expected to result in weak population structure. Here, we investigated population genetic structure of lumpfish throughout its natural distribution in the North Atlantic using two approaches: I) 4,393 genome wide SNPs and 95 individuals from 10 locations, and II) 139 discriminatory SNPs and 1,669 individuals from 40 locations. Both approaches identified extensive population genetic structuring with a major split between the East and West Atlantic and a distinct Baltic Sea population, as well as further differentiation of lumpfish from the English Channel, Iceland, and Greenland. The discriminatory loci displayed ~2–5 times higher divergence than the genome wide approach, revealing further evidence of local population substructures. Lumpfish from Isfjorden in Svalbard were highly distinct but resembled most fish from Greenland. The Kattegat area in the Baltic transition zone, formed a previously undescribed distinct genetic group. Also, further subdivision was detected within North America, Iceland, West Greenland, Barents Sea, and Norway. Although lumpfish have considerable potential for dispersal and gene-flow, the observed high levels of population structuring throughout the Atlantic suggests that this species may have a natal homing behavior and local populations with adaptive differences. This fine-scale population structure calls for consideration when defining management units for exploitation of lumpfish stocks and in decisions related to sourcing and moving lumpfish for cleaner fish use in salmonid aquaculture.

In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.

How an organism copes with chemicals is largely determined by the genes and proteins that collectively function to defend against, detoxify and eliminate chemical stressors. This integrative network includes receptors and transcription factors, biotransformation enzymes, transporters, antioxidants, and metal- and heat-responsive genes, and is collectively known as the chemical defensome. Teleost fish is the largest group of vertebrate species and can provide valuable insights into the evolution and functional diversity of defensome genes. We have previously shown that the xenosensing pregnane x receptor (pxr, nr1i2) is lost in many teleost species, including Atlantic cod (Gadus morhua) and three-spined stickleback (Gasterosteus aculeatus), but it is not known if compensatory mechanisms or signaling pathways have evolved in its absence. In this study, we compared the genes comprising the chemical defensome of five fish species that span the teleosteii evolutionary branch often used as model species in toxicological studies and environmental monitoring programs: zebrafish (Danio rerio), medaka (Oryzias latipes), Atlantic killifish (Fundulus heteroclitus), Atlantic cod, and three-spined stickleback. Genome mining revealed evolved differences in the number and composition of defensome genes that can have implication for how these species sense and respond to environmental pollutants, but we did not observe any candidates of compensatory mechanisms or pathways in cod and stickleback in the absence of pxr. The results indicate that knowledge regarding the diversity and function of the defensome will be important for toxicological testing and risk assessment studies.

Coexistence of fish populations (= stocks) of the same species is a common phenomenon. In the Baltic Sea, two genetically divergent stocks of Atlantic cod ( Gadus morhua ), Western Baltic cod (WBC) and Eastern Baltic cod (EBC), coexist in the Arkona Sea. Although the relative proportions of WBC and EBC in this area are considered in the current stock assessments, the mixing dynamics and ecological mechanisms underlying coexistence are not well understood. In this study, a genetically validated otolith shape analysis was used to develop the most comprehensive time series of annual stock mixing data (1977–2019) for WBC and EBC. Spatio-temporal mixing analysis confirmed that the two stocks coexist in the Arkona Sea, albeit with fluctuating mixing proportions over the 43-year observation period. Depth-stratified analysis revealed a strong correlation between capture depth and stock mixing patterns, with high proportions of WBC in shallower waters (48–61% in <20m) and increasing proportions of EBC in deeper waters (50–86% in 40-70m). Consistent depth-specific mixing patterns indicate stable differences in depth distribution and habitat use of WBC and EBC that may thus underlie the long-term coexistence of the two stocks in the Arkona Sea. These differences were also reflected in significantly different proportions of WBC and EBC in fisheries applying passive gears in shallower waters (more WBC) and active gears in deeper waters (more EBC). This highlights the potential for fishing gear-specific exploitation of different stocks, and calls for stronger consideration of capture depth and gear type in stock assessments. This novel evidence provides the basis for improved approaches to research, monitoring and management of Baltic cod stocks.

In this work, the potential of spectroscopic techniques was studied to investigate heat-induced changes occurring during the application of thermal treatments on cod (Gadus morhua L.) fillets. Vacuum-packed samples were thermally treated in a water bath at 50, 60, 70 and 80 °C for 5 and 10 min, and further stored for one, four, and eight days at 4 ± 1 °C before analysis. Several traditional (including cooking loss, drip loss, texture, protein solubility, protein oxidation, and color) and spectroscopic (fluorescence and diffuse reflectance hyperspectral imaging) measurements were conducted on the same samples. The results showed a decrease in fluorescence intensity with increasing cooking temperature and storage time, while the impact of cooking time was only noticeable at low temperatures. Diffuse reflectance data exhibited a decrease in absorbance, possibly as a result of protein denaturation and increased scattering at higher cooking temperatures. Both fluorescence and diffuse reflectance data were highly correlated with color parameters, whereas moderate correlations were observed with most other traditional parameters. Support vector machine models performed better than partial least square ones for both classification of cod samples cooked at different temperatures and in prediction of the cooking temperature. The best classification result was obtained on fluorescence data, achieving an accuracy of 92.5%, while the prediction models resulted in a root mean square error of prediction of cooking temperature lower than 5 °C. Overall, the classification and prediction models showed good results, indicating that spectroscopic techniques, especially fluorescence hyperspectral imaging, have a high potential for monitoring thermal treatments in cod fillets.